Pre-migration assurance
Identify missing keys, invalid values, duplicates and broken relationships before records reach a new platform.
02 · Data & Reporting
Data validation: Prove what is complete, consistent and fit for purpose - and surface what is not.
Lumaivo turns business expectations into repeatable data checks, reconciliation views and exception queues. Results are explained at record and rule level so people can correct, approve or deliberately accept the remaining risk.
What this service is for
Start with the business meaning, then make the technical route explicit.
A dataset can be technically valid and still be wrong for the decision it supports. Validation therefore starts with business use: which records should exist, which totals must reconcile, which relationships are mandatory, and which exceptions require human judgement.
We preserve the input, define rules with clear severity and ownership, run those checks repeatably, and separate trusted records from exceptions. The aim is not a decorative quality score. It is an actionable record of what passed, what failed and what needs a decision.
Where it becomes useful
Common use cases, framed around the decision or hand-off.
Reporting trust
Reconcile operational, CRM and finance outputs and show the records behind a disputed total.
Ongoing quality control
Run scheduled checks and route new exceptions to the people able to resolve them.
Method
A controlled route from discovery to an accepted output.
- 01
Define fitness
Agree what the data must support and which failures would make an output unsafe or misleading.
- 02
Specify checks
Document completeness, format, range, uniqueness, referential-integrity and reconciliation rules.
- 03
Baseline
Run the checks against an approved snapshot and classify existing failures without changing the source.
- 04
Investigate
Trace material exceptions back to source records, transformations or ownership decisions.
- 05
Control
Publish repeatable test results, acceptance thresholds and an exception workflow for future runs.
Typical deliverables
What the review-ready work can contain.
- Data-quality rule catalogue with severity and owner
- Validation queries or repeatable test routines
- Record-level exception output
- Cross-system reconciliation summary
- Accepted-risk and waiver register
- Rerunnable validation report for migration or reporting gates
Boundaries
What stays explicit instead of being over-promised.
- Quality is assessed against an agreed business purpose, not an invented universal score.
- Failed records remain traceable to the original source and rule.
- Automated correction is not enabled without explicit transformation rules and approval.
- Exceptions that require business judgement remain human decisions.
Questions before the first conversation
Plain answers, with the limits left in.
What types of validation can you run?
Typical checks cover completeness, permitted values, dates and ranges, uniqueness, referential integrity, cross-field logic, duplicate candidates and reconciliation to trusted totals.
Is data cleansing included?
The service can identify and classify cleansing needs. Corrections can be implemented as a separate controlled step once the business approves the rule, ownership and rollback approach.
Can validation run continuously?
Yes, where the source access and operating environment support it. We first prove the rules against a bounded snapshot, then design an appropriate schedule and exception route.
How do you handle duplicates?
We define candidate-match signals and confidence bands, preserve the original records and separate obvious matches from ambiguous cases that need review.
Can results be used as a migration gate?
Yes. The acceptance criteria can be tied to rehearsal, cutover and post-load reconciliation gates, with failed or waived checks recorded explicitly.
Related services
Continue through the connected system.
01 · Data & Reporting
Data mapping
Make every field, key, rule and ownership decision visible before building the next layer.
Read service 03 · Data & ReportingData migration
Move business-critical data through rehearsed, reconciled and reversible gates.
Read service 05 · Data & ReportingSQL reporting & dashboards
Build reports around trusted definitions, visible exceptions and the decisions people need to make.
Read serviceStart with the messy version. Make the first useful outcome explicit.
Send the systems, reports, constraints and decisions involved. Lumaivo will help define a bounded first step and the evidence needed to accept it.
Map the first useful step